M. Beaudor, N. Vuichard, J. Lathière, D. A. Hauglustaine
{"title":"气候变化下全球农业氨排放的未来趋势","authors":"M. Beaudor, N. Vuichard, J. Lathière, D. A. Hauglustaine","doi":"10.1029/2023MS004186","DOIUrl":null,"url":null,"abstract":"<p>Because of human population growth and changes in diet, global livestock and associated ammonia <span></span><math>\n <semantics>\n <mrow>\n <mfenced>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n </mfenced>\n </mrow>\n <annotation> $\\left(\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}\\right)$</annotation>\n </semantics></math>, emissions are projected to increase through the end of the century, with possible impacts on atmospheric chemistry and climate. In this study, we propose a methodology to project global gridded livestock densities and <span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n <annotation> $\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}$</annotation>\n </semantics></math> emissions from agriculture until 2100. Based on a downscaling method, future livestock distribution has been estimated until 2100 for three Shared Socio-economic Pathways (SSP2-4.5, SSP4-3.4, and SSP5-8.5) and used in a global process-based model (Calculation of AMmonia Emissions in ORCHIDEE, CAMEO) to estimate agricultural ammonia emissions during the 21st century. Emissions under SSP4-3.4 and SSP5-8.5 calculated by CAMEO compare well with the range estimated by the Integrated Assessment Models (IAM; 50 to 66 <span></span><math>\n <semantics>\n <mrow>\n <mi>T</mi>\n <mi>g</mi>\n <mi>N</mi>\n <mo>.</mo>\n <mi>y</mi>\n <msup>\n <mi>r</mi>\n <mrow>\n <mo>−</mo>\n <mn>1</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation> $\\mathrm{T}\\mathrm{g}\\mathrm{N}.\\mathrm{y}{\\mathrm{r}}^{-\\mathrm{1}}$</annotation>\n </semantics></math>) in the framework of the Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Some opposite trends arise under SSP2.4-5 where CAMEO emissions increase consistently in response to the increasing trends in synthetic fertilizer use under this scenario. Africa is identified as the most emitting region worldwide, with <span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n <annotation> $\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}$</annotation>\n </semantics></math> emissions ranging from 10 to 16 <span></span><math>\n <semantics>\n <mrow>\n <mi>T</mi>\n <mi>g</mi>\n <mi>N</mi>\n <mo>.</mo>\n <mi>y</mi>\n <msup>\n <mi>r</mi>\n <mrow>\n <mo>−</mo>\n <mn>1</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation> $\\mathrm{T}\\mathrm{g}\\mathrm{N}.\\mathrm{y}{\\mathrm{r}}^{-\\mathrm{1}}$</annotation>\n </semantics></math> in 2100. Through a set of simulations, we estimated climate change as responsible for 20 % of future increase in <span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n <annotation> $\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}$</annotation>\n </semantics></math> emissions. The produced data sets of future <span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n <annotation> $\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}$</annotation>\n </semantics></math> emissions is an alternative option to IAM-based emissions for studies aiming at projecting the evolution of atmospheric chemistry and its impact on climate. Further model developments involving the bi-directional property of <span></span><math>\n <semantics>\n <mrow>\n <mi>N</mi>\n <msub>\n <mi>H</mi>\n <mn>3</mn>\n </msub>\n </mrow>\n <annotation> $\\mathrm{N}{\\mathrm{H}}_{\\mathrm{3}}$</annotation>\n </semantics></math> and refinement in the future changes of agricultural practices constitute interesting perspectives.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 4","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023MS004186","citationCount":"0","resultStr":"{\"title\":\"Future Trends of Global Agricultural Emissions of Ammonia in a Changing Climate\",\"authors\":\"M. Beaudor, N. Vuichard, J. Lathière, D. A. Hauglustaine\",\"doi\":\"10.1029/2023MS004186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Because of human population growth and changes in diet, global livestock and associated ammonia <span></span><math>\\n <semantics>\\n <mrow>\\n <mfenced>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n </mfenced>\\n </mrow>\\n <annotation> $\\\\left(\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}\\\\right)$</annotation>\\n </semantics></math>, emissions are projected to increase through the end of the century, with possible impacts on atmospheric chemistry and climate. In this study, we propose a methodology to project global gridded livestock densities and <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n <annotation> $\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}$</annotation>\\n </semantics></math> emissions from agriculture until 2100. Based on a downscaling method, future livestock distribution has been estimated until 2100 for three Shared Socio-economic Pathways (SSP2-4.5, SSP4-3.4, and SSP5-8.5) and used in a global process-based model (Calculation of AMmonia Emissions in ORCHIDEE, CAMEO) to estimate agricultural ammonia emissions during the 21st century. Emissions under SSP4-3.4 and SSP5-8.5 calculated by CAMEO compare well with the range estimated by the Integrated Assessment Models (IAM; 50 to 66 <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>T</mi>\\n <mi>g</mi>\\n <mi>N</mi>\\n <mo>.</mo>\\n <mi>y</mi>\\n <msup>\\n <mi>r</mi>\\n <mrow>\\n <mo>−</mo>\\n <mn>1</mn>\\n </mrow>\\n </msup>\\n </mrow>\\n <annotation> $\\\\mathrm{T}\\\\mathrm{g}\\\\mathrm{N}.\\\\mathrm{y}{\\\\mathrm{r}}^{-\\\\mathrm{1}}$</annotation>\\n </semantics></math>) in the framework of the Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Some opposite trends arise under SSP2.4-5 where CAMEO emissions increase consistently in response to the increasing trends in synthetic fertilizer use under this scenario. Africa is identified as the most emitting region worldwide, with <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n <annotation> $\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}$</annotation>\\n </semantics></math> emissions ranging from 10 to 16 <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>T</mi>\\n <mi>g</mi>\\n <mi>N</mi>\\n <mo>.</mo>\\n <mi>y</mi>\\n <msup>\\n <mi>r</mi>\\n <mrow>\\n <mo>−</mo>\\n <mn>1</mn>\\n </mrow>\\n </msup>\\n </mrow>\\n <annotation> $\\\\mathrm{T}\\\\mathrm{g}\\\\mathrm{N}.\\\\mathrm{y}{\\\\mathrm{r}}^{-\\\\mathrm{1}}$</annotation>\\n </semantics></math> in 2100. Through a set of simulations, we estimated climate change as responsible for 20 % of future increase in <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n <annotation> $\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}$</annotation>\\n </semantics></math> emissions. The produced data sets of future <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n <annotation> $\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}$</annotation>\\n </semantics></math> emissions is an alternative option to IAM-based emissions for studies aiming at projecting the evolution of atmospheric chemistry and its impact on climate. Further model developments involving the bi-directional property of <span></span><math>\\n <semantics>\\n <mrow>\\n <mi>N</mi>\\n <msub>\\n <mi>H</mi>\\n <mn>3</mn>\\n </msub>\\n </mrow>\\n <annotation> $\\\\mathrm{N}{\\\\mathrm{H}}_{\\\\mathrm{3}}$</annotation>\\n </semantics></math> and refinement in the future changes of agricultural practices constitute interesting perspectives.</p>\",\"PeriodicalId\":14881,\"journal\":{\"name\":\"Journal of Advances in Modeling Earth Systems\",\"volume\":\"17 4\",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023MS004186\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Advances in Modeling Earth Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2023MS004186\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advances in Modeling Earth Systems","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2023MS004186","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Future Trends of Global Agricultural Emissions of Ammonia in a Changing Climate
Because of human population growth and changes in diet, global livestock and associated ammonia , emissions are projected to increase through the end of the century, with possible impacts on atmospheric chemistry and climate. In this study, we propose a methodology to project global gridded livestock densities and emissions from agriculture until 2100. Based on a downscaling method, future livestock distribution has been estimated until 2100 for three Shared Socio-economic Pathways (SSP2-4.5, SSP4-3.4, and SSP5-8.5) and used in a global process-based model (Calculation of AMmonia Emissions in ORCHIDEE, CAMEO) to estimate agricultural ammonia emissions during the 21st century. Emissions under SSP4-3.4 and SSP5-8.5 calculated by CAMEO compare well with the range estimated by the Integrated Assessment Models (IAM; 50 to 66 ) in the framework of the Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Some opposite trends arise under SSP2.4-5 where CAMEO emissions increase consistently in response to the increasing trends in synthetic fertilizer use under this scenario. Africa is identified as the most emitting region worldwide, with emissions ranging from 10 to 16 in 2100. Through a set of simulations, we estimated climate change as responsible for 20 % of future increase in emissions. The produced data sets of future emissions is an alternative option to IAM-based emissions for studies aiming at projecting the evolution of atmospheric chemistry and its impact on climate. Further model developments involving the bi-directional property of and refinement in the future changes of agricultural practices constitute interesting perspectives.
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